Quasi-4-dimension ionospheric modeling and its application in PPP

The version of record of this article, first published in Satellite Navigation, is available online at Publisher’s website: http://dx.doi.org/10.1186/s43020-022-00085-zIonospheric delay modeling is not only important for GNSS based space weather study and monitoring, but also an efficient tool to overcome the long convergence time of PPP. In this study, a novel model, denoted as Q4DIM (Quasi-4-dimension ionospheric modeling) is proposed for wide-area high precision ionospheric delay correction. In Q4DIM, the LOS (line of sight) ionospheric delay from a GNSS station network is divided into different clusters according to not only latitude and longitude, but also elevation and azimuth. Both GIM (global ionosphere map) and SID (slant ionospheric delay) that traditionally used for wide-area and regional ionospheric delay modeling, respectively, can be regarded as special case of Q4DIM by defining proper grids in latitude, longitude, elevation and azimuth. Thus, Q4DIM presents a resilient model that is capable for both wide-area coverage and high precision. Then four different sets of clusters are defined to illustrate the properties of Q4DIM based on 200 EPN stations. The results suggested that Q4DIM is compatible with the widely acknowledged GIM products. Moreover, it is proved that by inducting the elevation and azimuth angle dependent residuals, the precision of the 2-dimensional GIM-like model, i.e., Q4DIM-2D, is improved from around 1.5 TECU to better than 0.5 TECU. In addition, by treating Q4DIM as a 4-dimensional matrix in latitude, longitude, elevation and azimuth, its sparsity is less than 5%, thus guarantees its feasibility in a bandwidth-sensitive applications, e.g., satellite-based PPP-RTK service. Finally, the advantage of Q4DIM in single frequency PPP over the 2-dimensional models is demonstrated with one month’s data from 30 EPN stations.Peer ReviewedPostprint (published version

Integer Ambiguity Resolution for Multi-GNSS and Multi-Signal Raw Phase Observations

The continuous modernisation of existing Global Navigation Satellite Systems (GNSS) and the development of new systems with a multitude of different carrier frequencies and a variety of signal modulations creates a true multi-GNSS and multi-signal environment available today. Still most precise GNSS processing strategies rely on dual-frequency measurements only by applying the Ionosphere-Free (IF) Linear Combination (LC) of GNSS observables and therefore do not benefit from the available multi-signal environment. While in this processing approach the first order effect of the ionospheric delay can be eliminated almost completely, the formation of linear combinations of GNSS observables leads to a noise increase for the resulting observations and a loss of some of the physical characteristics of the original signals, like the integer nature of the carrier phase ambiguity. In order to benefit from the multi-GNSS and multi-signal environment available today, the scientific analyses and precise applications presented in this work are based on the raw observation processing approach, which makes use of the original (raw) observations without forming any linear combinations or differences of GNSS observables. This processing strategy provides the flexibility to make use of all or a selection of available multi-GNSS and multi-signal raw observations, which are jointly processed in a single adjustment as there is no inherent limitation on the number of usable signals. The renunciation of linear combinations and observation differences preserves the physical characteristics of individual signals and implies that multi-signal biases and ionospheric delays need to be properly determined or corrected in the parameter estimation process. The raw observation processing approach is used in this work to jointly process measurements from up to three different GNSS, including eleven signals tracked on up to eight different carrier frequencies in one single adjustment. The bias handling for multi-GNSS and multi-signal applications is analysed with a focus on physically meaningful parameter estimates to demonstrate the benefits of handling clock offset parameters, multi-signal code biases and ionospheric delay estimates in a physically meaningful and consistent way. In this context, receiver-specific multi-GNSS and multisignal biases are analysed and calibrated by the use of a GNSS signal simulator. The disadvantages of eliminating physical characteristics due to the formation of linear combinations of observations or commonly used parameter estimation strategies are demonstrated and discussed. The carrier phase Integer Ambiguity Resolution (IAR) approach developed and implemented in the course of this work is based on the joint processing of multi-GNSS and multi-signal raw observations without forming any linear combinations or observation differences. Details of the implemented IAR approach are described and the performance is analysed for available carrier signal frequencies of different GNSS. Achieved results are compared to the conventional IAR approach based on IF linear combinations and the so called Widelane (WL) and Narrowlane (NL) ambiguities. In addition, the resolution of inter-system integer ambiguities is analysed for common GNSS signal frequencies. The performance of the implemented IAR approach is demonstrated and analysed by the joint Precise Orbit Determination (POD) of multi-GNSS satellites based on fixed multi-frequency carrier phase ambiguities. The improvement of the satellite orbit and clock quality by fixing raw observation ambiguities confirms the successful implementation of the IAR approach based on raw observation processing. Multi-GNSS satellite orbits and clock offsets determined with this approach are compared to results generated with the conventional IF linear combination processing approach and independent external products. This comparison demonstrates an at least equivalent performance of the implemented IAR approach based on raw observation processing. In addition, the fixed raw observation ambiguities are used to investigate and discuss characteristics of multi-GNSS and multi-frequency phase biases

Next Generation Multi-System Multi-Frequency GNSS Receivers

Nowadays we have satellites available from GPS, GLONASS, Galileo and BeiDou systems. This will lead to an increased demand for solutions, which utilize multiple Global Navigation Satellite Systems (GNSS). Such solutions can have great market potential since they can be applied in numerous applications involving GNSS navigation, e.g. smartphones and car navigators. The aim of this thesis is to present the issues that arise in modern high sensitivity receivers, and to present research results of navigation algorithms suitable for the next generation multi-system multi-frequency GNSS receivers.With the availability of multiple satellites systems, the user benefits mostly from the improved visibility of the satellites. The increased availability of satellites naturally increases the computational requirements in the receiver. The main focus of the presented algorithms is on critical factors like provided accuracy versus low cost, low power consumption. In addition, the presented algorithms have been collected into a comprehensive navigation algorithm library where they have additional value for educational purposes.The presented navigation algorithms focus mainly in the GPS and Galileo systems, with the combination of L1/E1 & L5/E5a frequencies. A novel GPS + Galileo dual frequency receiver was developed by the team over the years. Where applicable, the thesis collects important facts from modern GLONASS and BeiDou systems.The first part of the thesis introduces all available open service signals from the GNSS systems, revealing how vast the scope of multi-system, multi-frequency receiver design is. The chapter continues with introduction to the basics of GNSS systems, and description of the problems that the receiver designer must overcome. The chapter further continues by describing a basic receiver architecture suitable for multi-system multi-frequency reception. The introductory part also has a short section is dedicated for underlining the importance of testing mechanisms for a novel receiver under development.The second part of the thesis concentrates on the baseband processing of the GNSS receiver. Topics cover acquisition and tracking, with multi-system multi-frequency implementation Abstract details kept in mind. The chapter also contains sections for issues that must be handled in high sensitivity receivers, e.g. cross-correlation and cycle slip detection. The second part of the thesis is concluded with a description how Assisted-GNSS capability would alter many of the design considerations.The third part of the thesis describes algorithms related to the data bit decoding issues. All the different satellite systems have their own low-level navigation data structure with additional layers of error detection / correction mechanisms. This part of the thesis provides the algorithms for successful decoding of the data.The final part of the thesis describes the basic navigation solution algorithms suitable for the mass-market receivers. In this part, the method of combining the measurements from the different satellite systems is discussed. Additionally, all the issues of processing multisystem signals are collected here, and in the end the Position, Velocity, and Time (PVT) solution is obtained

Probabilistic snapshot GNSS for low-cost wildlife tracking

Snapshot GNSS is more energy-efficient than conventional localisation methods based on global navigation satellite systems (GNSS), like the GPS. This is beneficial for long deployments on battery such as in wildlife tracking. However, only a few snapshot GNSS systems that could be used for wildlife tracking have been presented and all have disadvantages. Most significantly, they are closed-source and either not available or expensive. A reason is that they typically require GNSS signals to be captured with good resolution, which demands complex receiver hardware capable of capturing multi-bit data at sampling rates of 16 MHz and more. By contrast, this thesis presents fast algorithms that reliably estimate locations from twelve-millisecond signals that are sampled at just 4 MHz and quantised with only a single bit. This allows to build a snapshot receiver at an unmatched low cost of less than $30 and with particularly low power consumption, outperforming existing systems and enabling low-budget and long-term field work. The system can acquire two positions per hour for a year on a tiny 40 mAh battery. On a challenging public dataset with thousands of snapshots from real-world scenarios, median accuracy is 11 m, comparable to more complex and expensive solutions with higher energy consumption. Additionally, the system has been deployed for several wildlife tracking studies, including on sea turtles, where brief signal acquisition times are crucial to obtain location fixes during surfacing events lasting only 1–2 s. For the first time, (i) snapshot GNSS receiver hardware and (ii) an accompanying cloud-based processing platform are open-source. This allowed several third parties to independently replicate the system. In total, several hundred receivers have been built and millions of locations estimated for those. As three additional contributions, this thesis presents (i) the first evaluation of snapshot GNSS for wildlife tracking across a variety of species and habitats, (ii) the first snapshot GNSS system with cloud-offloading via a low-power narrow-band cellular connection, and (iii) a demonstration of the potential of smoothing for snapshot GNSS. A final contribution are factor graph optimisation algorithms to (i) smooth snapshot GNSS data and (ii) tightly fuse raw GNSS data with inertial measurements and, optionally, lidar observations for precise and smooth localisation. In several environments with little sky visibility, such as a forest, the accuracy of the fused location estimates in the global Earth frame is still 1–2 m, while the estimated trajectories are discontinuity-free and smooth. This requires a professional-grade (non-snapshot) GNSS receiver, but, unlike traditional differential GNSS, no connection to a base station

Precise Point Positioning Augmentation for Various Grades of Global Navigation Satellite System Hardware

The next generation of low-cost, dual-frequency, multi-constellation GNSS receivers, boards, chips and antennas are now quickly entering the market, offering to disrupt portions of the precise GNSS positioning industry with much lower cost hardware and promising to provide precise positioning to a wide range of consumers. The presented work provides a timely, novel and thorough investigation into the positioning performance promise. A systematic and rigorous set of experiments has been carried-out, collecting measurements from a wide array of low-cost, dual-frequency, multi-constellation GNSS boards, chips and antennas introduced in late 2018 and early 2019. These sensors range from dual-frequency, multi-constellation chips in smartphones to stand-alone chips and boards. In order to be comprehensive and realistic, these experiments were conducted in a number of static and kinematic benign, typical, suburban and urban environments. In terms of processing raw measurements from these sensors, the Precise Point Positioning (PPP) GNSS measurement processing mode was used. PPP has become the defacto GNSS positioning and navigation technique for scientific and engineering applications that require dm- to cm-level positioning in remote areas with few obstructions and provides for very efficient worldwide, wide-array augmentation corrections. To enhance solution accuracy, novel contributions were made through atmospheric constraints and the use of dual- and triple-frequency measurements to significantly reduce PPP convergence period. Applying PPP correction augmentations to smartphones and recently released low-cost equipment, novel analyses were made with significantly improved solution accuracy. Significant customization to the York-PPP GNSS measurement processing engine was necessary, especially in the quality control and residual analysis functions, in order to successfully process these datasets. Results for new smartphone sensors show positioning performance is typically at the few dm-level with a convergence period of approximately 40 minutes, which is 1 to 2 orders of magnitude better than standard point positioning. The GNSS chips and boards combined with higher-quality antennas produce positioning performance approaching geodetic quality. Under ideal conditions, carrier-phase ambiguities are resolvable. The results presented show a novel perspective and are very promising for the use of PPP (as well as RTK) in next-generation GNSS sensors for various application in smartphones, autonomous vehicles, Internet of things (IoT), etc

A Review of Selected Applications of GNSS CORS and Related Experiences at the University of Palermo (Italy)

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years

An Evaluation of Optimization Algorithms for the Optimal Selection of GNSS Satellite Subsets

The continuous advancements of GNSS systems have led, apart from the broadly used GPS, to the development of other satellite systems (Galileo, BeiDou, GLONASS), which significantly increased the number of the available satellites for GNSS positioning applications. However, despite the GNSS satellites redundancy, potential poor GNSS satellite signal (i.e. low signal-to-noise ratio) can negatively affect the GNSS performance and the positioning accuracy. On the other hand, the selection of high-quality GNSS satellite signals by retaining a sufficient number of GNSS satellites can enhance the GNSS positioning performance. Various methods, including optimization algo-rithms, which are also commonly adopted in artificial intelligence (AI) methods, have been applied for satellite selection. In this paper, five optimization algorithms were investigated and assessed in determining the optimal GNSS satellite constellation, such as Artificial Bee Colony optimization (ABC), Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm (PSO) and Sim-ulated Annealing (SA). The assessment of the optimization algorithms was based on two criteria, such as the robustness of the solution for the optimal satellite constellation and the time required to find the solution. The selection of the GNSS satellites was based on the weighted geometric dilution of precision (WGDOP) parameter, where the geometric dilution of precision (GDOP) is modified by applying weights based on the quality of the satellites’ signal. The optimization algorithms were tested on the basis of 24-hours of tracking data gathered from a permanent GNSS station, for GPS-only and multi-GNSS data (GPS, GLONASS, and Galileo). According to the comparison results, ABC, ACO, and PSO algorithms were equivalent in terms of selection accuracy and speed. How-ever, ABC was considered to be the most suitable algorithm due to the fewest number of parameters that are required to be set. To further investigate ABC performance, the method was applied for the selection of an optimal GNSS satellite subset according to the number of total available tracked GNSS satellites (up to 31 satellites), leading to more than 300 million possible combinations of 15 GNSS satellites. ABC was able to select the optimal satellite subsets with 100% accuracy

Satellite Selection Methodology for Horizontal Navigation and Integrity Algorithms

With the new upcoming GNSS constellation in the future it might no longer be possible to use all satellites in view for navigation due to limited tracking channels. This is in particular true in the context of Advanced Receiver Autonomous Integrity Monitoring (ARAIM), where the use of dual frequency is favorable to mitigate ionospheric disturbances. To address the issues of limited channels we propose two different satellites selection strategies adapted for Horizontal ARAIM in this paper. First a bare geometric approach which comes with almost no additional computation effort at the cost of less stable results. And second a heuristic optimization which improves selection results significantly while adding additional computational effort. Both approaches are compared to brute force selected best sets in terms of resulting protection levels, computational cost and achieved ARAIM availability. Results show the general applicability of both presented selection methods in Horizontal ARAIM. Using limited sets instead of all satellites in view can still provide global availability. Depending on the method more or less satellites are necessary to ensure sufficiently small and stable protection levels

Navigation Constellation Design Using a Multi-Objective Genetic Algorithm

In satellite constellation design, performance and cost of the system drive the design process. The Global Positioning System (GPS) constellation is currently used to provide positioning and timing worldwide. As satellite technology has improved over the years, the cost to develop and maintain the satellites has increased. Using a constellation design tool, it is possible to analyze the tradeoffs of new navigation constellation designs (Pareto fronts) that illustrate the tradeoffs between position dilution of precision (PDOP) and system cost. This thesis utilized Satellite Tool Kit (STK) to calculate PDOP values of navigation constellations, and the Unmanned Spacecraft Cost Model (USCM) along with the Small Spacecraft Cost Model (SSCM) to determine system cost. The design parameters used include Walker constellation parameters, orbital elements, and transmit power. The results show that the constellation design tool produces realistic solutions. Using the generated solutions, an analysis of the navigation constellation designs was presented